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Robustno cjelobrojno programiranje×Mješovito cjelobrojno programiranje×
PodručjeSimulacijaSimulacija
ObiteljProcess / pipelineProcess / pipeline
Godina nastanka20031958–1960
TvoracBertsimas, D. and Sim, M.Ralph Gomory (branch-and-bound cuts, 1958); Land & Doig (branch-and-bound, 1960)
VrstaDeterministic robust optimization with integer variablesMathematical optimization
Temeljni izvorBertsimas, D., Sim, M. (2003). Robust discrete optimization and network flows. Mathematical Programming, 98(1-3), 49-71. DOI ↗Nemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. Wiley-Interscience, New York. ISBN: 9780471359432
Drugi naziviRIP, Robust IP, Robust Combinatorial Optimization, Integer Robust OptimizationMIP, Mixed-Integer Linear Programming, MILP, Integer Programming
Srodne66
SažetakRobust Integer Programming (RIP) finds integer or binary solutions that remain feasible and near-optimal across all scenarios in a prescribed uncertainty set. Rather than assuming exact knowledge of data, RIP hedges against the worst-case realization of uncertain costs or constraint coefficients, delivering decisions that are guaranteed to perform well even when inputs deviate from their nominal values.Mixed-Integer Programming (MIP) is a mathematical optimization framework in which some decision variables must take integer values while others may be continuous. It generalizes linear programming and is widely used in operations research, logistics, scheduling, resource allocation, and engineering design, where indivisibility constraints — such as yes/no decisions or whole-unit quantities — arise naturally.
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ScholarGateUsporedite metode: Robust Integer Programming · Mixed-Integer Programming. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare